# Pipeline Design

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26-Nov-2014Category

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On a New Methodology for the Design and Operations Planning of Natural Gas Pipeline NetworksDbora Campos de Faria, Kristy Booth, Chase Waite and Miguel Bagajewicz*Department of Chemical Biological and Materials Engineering University of Oklahoma

Kewords: Pipeline Design (*) Corresponding author: bagajewicz@ou.edu

ABSTRACT This paper presents a new methodology to design natural gas pipelines over a long time horizon considering determining timely expansions by the addition of compressors. The problem is framed in the context of a capacity expansion problem and is solved using a non-linear mixed integer model. We compare our methodology to the current state-ofthe-art methodologies, highlighting the limitations of the latter and showing the advantages of the former, especially in the case of branched networks.

1. INTRODUCTION The economical design of pipelines is important because the cost for transmission and distribution is almost half of the total price the end user pays for natural gas. The United States consumes between 1.5 and 2.5 million MMcf of natural gas per month depending on the season, and this huge volume has to be transported somehow to the end user1. About 97 % of the natural gas consumed in the U.S. is produced at various places in North America. So, there is no hub where all the gas is produced, the producing sites are constantly changing their rates and producing status and new wells are also constantly being discovered. Currently, it is common to

examine the feasibility of projects based on J-curves which analyze the Total Annual Cost per MCF transported versus the flow rate. This type of analysis can be sufficient for a simple project with no ramifications and a single pipe. But when analyzing a more complicated network, J-curves become exponentially more time consuming, and many times will not even give the correct optimum.

2. PROBLEM STATEMENT We now discuss different cases:

a. Conventional structure In this case the pipeline routes and compressors locations are predefined, but initial capacities and expansion capacities (size and timing) are not. Compressors are located only at the supplier points and or some consumer or recompression station points. We want to know the optimum pipeline diameters for each section and the compressors capacities at the suppliers. Branching and non branching structures can be analyzed. The following diagram serves as an example of the conventional design approach, from the planning stage to some time t*.

Cap? W?

D?

D? D?

D = 32

D=32 D=28

F=75 Input DataD = 32 D = 32 D = 28 Cap = 4000 W = 2500

F=57 F=32 t=0

Consumer point without a compressor Compressor Station Cap = Compressor size

F=80Cap = 4000 W = 3500

F=63 F=45

D = Pipe diameter F = Flow rate W = Required work

t=t* t=t*

In the above example, the maximum compressor capacity and required diameters are computed. When the demand increases at time t*, the work of the compressor

increases, while the capacity and diameters remain constant.

b. Compressor location

The pipeline routes are predefined. We want to know the pipeline sections diameters and where, when and with which capacity a compressor should be installed.

Cap? W?

D?

D? D?

D = 32

D=32 D=28

F=75

F=57 F=32

Input DataD = 32 D = 32 D = 28

Cap = 4000 W = 2500

t=0

Consumer point with possible compressor These locations are predefined as consumer points but may require compressors under future demands W1 = Work required at first compressor

F=80

F=63 F=45

Cap1 = First compressor size W2 = Work required at second compressor Cap2 = Second compressor size

Cap1 = 4000 W1 = 3500

t=t*

Cap2 =2000 W2 =1500

t=t*

F = Flow rate, MMSCFD

During the design phase, the consumer points are predefined. It is unknown if a compressor is required at any of these points. By time t=0, a compressor is required at the supply point, yet the possible increase in demand may require further addition of compressors at the consumer points. At time t=t*, a second compressor is added, and all other consumer points are no longer available for adding compressors.

c. Loop and compressors locations The pipeline routes are predefined. We want to know the pipeline diameters; where, when and with which capacity a compressor should be installed; and, where, when and which capacity loops should be added. During the design phase, two possible loops are considered in this example. The route has already been determined, but an increase in

demand may require one or both of the loops at a later time. At time t=0, adding the supply compressor determines that only one loop will be further considered. The remaining consumer points are still available for adding compressor as required. At time t=t* the increase in demand requires greater work at the compressor. The pipe diameters at t=t* are slightly varied from those of t=0. The maximum required diameter must be chosen for operation.

Cap? W?

D?

D? D?

D = 32

D=32 D=28

F=75

F=57 F=32

Input Data

Cap = 4000 W = 2500

t=0

D = 28 D = 32 D = 32 D = 24

Consumer point with possible compressor These locations are predefined as consumer points but may require compressors under future demands Possible loop W1 = Work required at first compressor Cap1 = First compressor size W2 = Work required at second compressor Cap2 = Second compressor size F = Flow rate, MMSCFD

F=80

F=63 F=45

Cap1 = 4000 W1 = 3500

t=t* Cap

2 =2000 W2 =1500

t=t*

d. Alternative routes, loops and compressors locations Only the consumers and suppliers distances are predefined. We want to know where, when and with what capacity pipelines (including loops) and compressors should be installed. The possible loops and alternative routes are shown in the input data. At time t=0, an alternative route is chosen, but the consumer points are shown as having the option of adding a compressor. By t=t*, a second compressor is added and the other consumer points are not available for compressor addition.

D=28

Cap? W?

D?

D? D?

D = 32

D=32

F=75

F=57 F=32

Input DataD = 28

Cap = 4000 W = 2500

t=0

D = 24 D = 32 D = 32

Consumer point with possible compressor These locations are predefined as consumer points but may require compressors under future demands Possible loop or alternative route W1 = Work required at first compressor Cap1 = First compressor size W2 = Work required at second compressor Cap2 = Second compressor size F = Flow rate, MMSCFD

F=80

F=63 F=45

Cap1 = 4000 W1 = 3500

Cap t=t* 2

=2000 W2 =1500

t=t*

In this paper only cases a and b will be approached. The others are subject for further study.

3. PIPELINE DESIGN BASICS Typically, to calculate the pressure drops, the literature recommends using the Panhandle A equation (for Reynolds numbers between 5 and 11 million)

(1) and the Panhandle B equation (suitable for Reynolds numbers between 4 and 40 million)4.

(2) In these equations, Q volume flow rate (SCFD) E the Pipeline efficiency Pb the base pressure (psia) Tb the base temperature (R) P1 the upstream pressure (psia) P2 the downstream pressure (psia) G the gas gravity Tf the average gas flow temperature (R) Le the equivalent length of pipe segment (miles) Z the gas compressibility factor (dimensionless) D the pipe inside diameter (in) e = base of natural logarithms (e=2.718) s = elevation adjustment parameter, dimensionless

The elevation adjustment parameter is found from the following equation:

Where H1 is the upstream elevation (m) H2 is the downstream elevation (m) The panhandle equations were derived from simplifications of the Bernoulli equation. In its most inclusive form, the Bernoulli is as follows:

In order to arrive at the panhandle equations above, specific transmission factors are used. For the Panhandle A equation, the transmission factor is 6.872(Re)0.0730. For the Panhandle B equation, the transmission factor is 16.49(Re)0.01961. The constant values

of the panhandle equations are dependent on an assumed viscosity, as well as the assumption that

.

Qb is assumed to be at base conditions, with a base temperature of 520R and a base pressure of 14.7 psia. Besides these pressure drop correlations, simulation software can also be used. Here we compare the results using the Panhandle correlations to the ones found using simulations from Pro/II. The simulations used the Beggs-Brill-Moody pressure drop correlation, which is good for mostly vapor hydrocarbon systems with small elevation changes, very similar to this situation. We used the Soave-Redlich-Kwong

thermodynamic equation of state, which is suitable for hydrocarbon systems such as the one being examined. A negligible pipe roughness was assumed, along with a length of 120 miles, a composition listed in Table 1, an outlet pressure of 800 psig, an inlet temperature of 60 F, a viscosity of 7.53 x 10-7 lb/ft/s, and a pipeline efficiency of 0.922,3,4. An overall coefficient of heat transfer was assumed to be 0.3 Btu/hr-ft2-F based on rough calculations using the correlation by Churchill and Chu6. Table 1 Natural Gas Composition Used5 Natural Gas Component C1 C2 C3 N2 CO2 C4 iC4 C5 iC5 O2 Mole Fraction 0.949 0.025 .002 0.016 0.007 0.0003 0.0003 0.0001 0.0001 0.0002

The two independent methods, Pro-II simulation and analytical correlations, were used to predict these pressure drops. Both methods were analyzed by the s